Skip to main content

Arsha Bharatha Avengers

Indians, countrymen! Lend me your attention. For I am here to show you how Marvel Comics have exploited our vast mythology to come up with their league of superheroes, known as The Avengers.

As you may be aware, The Avengers consists of Captain America, Iron Man, Thor, Incredible Hulk, Hawk Eye, Black Widow and Ant Man. What you may not have realized the characterization of each of these superheroes was influenced by our own folklore. 

drink up me hearties yo ho

I assume you to be pretty skeptical at this point. So let us introspect each of them closely (and hopefully wipe that smirk off your face).

Captain America: A veteran soldier who participated in the World War II, and then entered a state of seemingly endless sleep that lasted seven decades. He was recalled by S.H.I.E.L.D when they needed his services for another possibly catastrophic war.

Those who have read The Ramayana would be familiar with the character of Kumbhakarna, the younger brother of demon king Ravana who was awaken from his six month slumber by the Lanka troops to get him ready for the final battle with Lord Ram.

Iron Man: The billionaire philanthropist Tony Stark gets a tad unlucky when he is kidnapped. To escape captivity, he designs a powered suit of armor. When suited up, defeating Iron Man is a herculean task.

If we list out the unlucky characters from The Mahabharata, my bet is on Karna to top the list. He is a master in archery, and is literally indestructible when he wears his armor and earrings gifted by his godfather, The Sun.

Thor and Loki: Marvel themselves have confessed that these two characters have been taken from the Norse mythology. Yet if we are to consider the fact that these two half brothers fight each other, arguing who among them is the true king, one cannot be blamed if he/she is to relate Thor and Loki to Yudhishtira and Dhuryodhana.

Incredible Hulk: Here, the Marvel guys have done a smarter work, as Hulk is a culmination of 2 different avatars from our legends. The brute physical strength of Hulk is an obvious inspiration from Bheema.

But one must not forget that Dr. Banner turns into the all destructive Hulk when he unleashes the rage within. Lord Shiv is also popular for his third eye, which when opened in seething rage lets out an all consuming flame.

Hawk Eye: Hawk is a bird known for its excellent eyesight and ability to locate preys from huge distances. Hawkeye is a master in archery. Needless to say, this "hero" is the Marvel version of Pandava prince Arjuna, who is well known for his skills with the bow and arrow.

Black Widow: I must admit, here the play by Marvel is so subtle that one begins to wonder she is original after all. But on deeper prodding, we can find some similarities with Droupadi. 

Droupadi was also known as Krishna, due to her dark complexion. Krishna means black in Sanskrit. See? Also, Mahabharata suggests that among the Pandavas, Droupadi had a soft corner towards Arjuna. The Avengers too seem to follow this, by showing a special bond between Black Widow and Hawkeye.

Ant Man: The latest addition to the team has the super-power of being able to shrink down to the size of an ant, and grow up to gigantic proportions.

Lord Hanuman is also said to have the exact same powers in both The Ramayana as well as The Mahabharata.

That's it. I rest my case.


Comments

Popular posts from this blog

Machine Unlearning #0 (Intro)

You might be familiar with the term Machine Learning. Worry not if you have not, cause I have tried to give a gist of the concept here. The term has been in the limelight of late and has been tossed around rather liberally to denote anything related to artificial intelligence, robotics, and data mining. Machine Learning, as the name suggests, could simply mean the field of study of enabling the “machines” (computers) to “learn” from past experiences and make informed decisions in the future.   Wait a minute! Learning from past experiences is something humans do, right? Exactly! The computer folks want computers to behave more and more like us. As if there aren't enough of us already. As the machines are becoming more like us, we are becoming more like them. Introspection time! Most of us wake up every morning like clockwork! Then we rush through the morning routines - get dressed, wade through the traffic, and reach our offices or schools or wherever people expect us to be. We spe

The High State

 Before The Judgement I believe I must begin by addressing the pressing question - Was planning a vacation in the midst of a pandemic a recommended move?  No. Yet we went ahead with it. Here is why.  We (Nithya & I) were newly married, and our vividly planned vacation at the island of Langkawi was stolen away from us by the virus. Our stay in Delhi was coming to an end due to job-related moves, and we felt it would be a waste not to utilize this opportunity in exploring at least one of the tourist hot spots easily accessible from the national capital region. Let us end this section by answering another question - Are the reasons listed above good enough to risk a vacation during a pandemic? No. We had taken a calculated risk. Arrival at Manali There are two phases to this - planning and execution. We had not started planning with Manali in mind. There were numerous choices - starting from Jaipur and Amritsar to Nainital, Shimla, and Manali. After a bit of reading and deliberations,

Machine Unlearning #1 (Classification)

You can’t conclude a discussion on Machine Learning without mentioning classification. Classification is a machine learning technique where the machine is trained to predict the label of the given input data. Alright, let’s cut the jargon and get some real-world examples. Oranges and Bananas. Let’s assume that we have a box of fruits that contain some oranges and some bananas. You are asked to pick one fruit at random and tell if it is an orange or a banana. Pretty basic, right? For us, it is straightforward. We would know the answer at first sight. But, how would a computer be able to tell the difference? In classification, the machine would first be trained on some pre-labeled data. It would be shown an orange and we would tell it that the fruit is an orange. The machine would study the orange and remember its features - orange color and round shape. Then it would be shown a banana and the process is repeated. What are these features? A feature is anything that helps us uniquely labe